Sylvia, KS
How exposed is Sylvia to wildfire?
Out of every US place USFS scores, Sylvia lands at the 96th percentile for wildfire risk to structures — in USFS's highest wildfire-risk band nationally — a figure built from its 223 buildings, not the land around them. (Source: USFS's Wildfire Risk to Communities methodology.)
Fire likelihood alone (USFS's burn-probability figure) ranks Sylvia at the 93rd national percentile — 3 points below its risk-to-structures score, a gap driven by how much is actually built there.
Where Sylvia's buildings actually sit
Only 16.1% of Sylvia's 223 buildings carry Direct exposure and 0% carry Indirect; the remaining 83.9% are Minimal, which shifts the risk driving this page's score toward the surrounding landscape rather than any one structure.
Sylvia against the rest of the country
There's little gap between Sylvia's 96th national percentile and its 98th percentile inside Kansas, which means the state comparison mostly confirms what the national score already shows. Among the 31,521 US communities USFS scores, Sylvia ranks 1,290 for wildfire risk (1 is highest) and 24,012 by building count (1 is largest). Within Kansas alone, it ranks 20 of 721 places by risk. See the full county-by-county picture for Kansas on its state page.
What this risk score means for insurance
At the 96th percentile nationally, Sylvia carries the very high rating that has pushed some carriers to limit new business in similarly-scored places elsewhere in the country. Worth comparing quotes rather than assuming last year's renewal terms still apply.
Lowering exposure, not just insuring around it
With 83.9% of buildings rated Minimal exposure, Sylvia gets less benefit from structure hardening than a Direct- or Indirect-dominant place would — the home-hardening guide explains why the zone matters.
Where Sylvia's figures come from
Sylvia's 96th-percentile score and its burn-probability figure both come from the same USFS workbook, documented in the methodology guide. The exposure-zones guide covers what Sylvia's dominant minimal exposure actually means, with real examples from across the dataset.